DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine

Recent global developments underscore the prominent role big data have in modern medical science. But privacy issues constitute a prevalent problem for collecting and sharing data between researchers. However, synthetic data generated to represent real data carrying similar information and distribut...

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Veröffentlicht in:	Scientific reports Jg. 11; H. 1; S. 21896 - 8
Hauptverfasser:	Thambawita, Vajira, Isaksen, Jonas L., Hicks, Steven A., Ghouse, Jonas, Ahlberg, Gustav, Linneberg, Allan, Grarup, Niels, Ellervik, Christina, Olesen, Morten Salling, Hansen, Torben, Graff, Claus, Holstein-Rathlou, Niels-Henrik, Strümke, Inga, Hammer, Hugo L., Maleckar, Mary M., Halvorsen, Pål, Riegler, Michael A., Kanters, Jørgen K.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 09.11.2021 Nature Publishing Group Nature Portfolio
Schlagworte:	631/114 631/114/1305 631/443/592 Computer Simulation Datasets as Topic Deepfake Electrocardiography Humanities and Social Sciences Humans multidisciplinary Neural networks Neural Networks, Computer Population studies Privacy Science Science (multidisciplinary)
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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